{"id":167983,"date":"2014-10-01T00:00:00","date_gmt":"2014-10-01T00:00:00","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/msr-research-item\/determination-of-room-impulse-response-for-synthetic-data-acquisition-and-asr-testing\/"},"modified":"2018-10-16T21:05:47","modified_gmt":"2018-10-17T04:05:47","slug":"determination-of-room-impulse-response-for-synthetic-data-acquisition-and-asr-testing","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/determination-of-room-impulse-response-for-synthetic-data-acquisition-and-asr-testing\/","title":{"rendered":"Determination of Room Impulse Response for synthetic data acquisition and ASR testing"},"content":{"rendered":"<div class=\"asset-content\">Automatic Speech Recognition (ASR) works best when the speech signal best matches the ones used for training. Training, however, may require thousands of hours of speech, and it is impractical to directly acquire them in a realistic scenario. Instead, we estimate Room Impulse Responses (RIRs), and convolve speech and noise signals with the estimated RIRs. This produces realistic signals, which can then be processed by the audio pipeline, and used for ASR training. In our research, a limited corpus of speech data as well as noise sources is recorded and the RIR at\u00a0 27 positions is determined using a variety of methods (chirp, MLS, impulse, and noise). The convolved RIR with the \u201cclean speech\u201d is compared to the actual measurements.<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Automatic Speech Recognition (ASR) works best when the speech signal best matches the ones used for training. Training, however, may require thousands of hours of speech, and it is impractical to directly acquire them in a realistic scenario. Instead, we estimate Room Impulse Responses (RIRs), and convolve speech and noise signals with the estimated RIRs. 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